research repository taxonomy

Research Repositories 101

July 5, 2024 2024-07-05

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As a research function scales, managing the growing research-related body of knowledge becomes a challenge. It’s common for research insights to get lost in hard-to-find reports. When this happens, research efforts are sometimes duplicated. Enter research repositories: an antidote to some of these common growing pains.

In This Article:

What is a research repository, what is included in a research repository, tools for research repositories, research-repository types, helpful features for successful adoption, 4 steps for creating a research repository.

A research repository is a central place where user-research artifacts and outputs are stored so that they can be accessed by others in the organization.

Storing user research centrally in a repository provides the following benefits:

• Insight can be quickly found because research outputs are stored in one place (rather than distributed across many platforms or team spaces).
• Teams can track findings and observations over time and across studies, helping to uncover themes that might not be identified from one study alone.
• Research efforts are not duplicated, as teams can learn from or build on research performed by others.

Creating and maintaining a research repository is often the responsibility of a ResearchOps function.

When successfully implemented, a research repository can be a helpful tool in increasing the UX maturity of an organization, because it makes insights about users accessible to many people.

Research repositories often house (or link out to) the following items:

• Research reports capture what happened and what was learned in the research study. A research report usually includes overarching themes, detailed findings, and sometimes recommendations.
• Research insights are the detailed findings acquired from each research study. While insights also appear in reports, saving them as their own entities makes them easier to see and address.
• Study materials, such as research plans and screeners, allow team members to learn how research insights were gathered and easily replicate a study method.
• Recordings, clips, and transcriptions make user data easily accessible. Summarizing and transcribing each video allows teams to search for keywords or specific information.
• Raw notes and artifacts from research sessions might be useful for future analysis and can sometimes be easier to read or process than a full transcript or video recording.

Of course, there could be other items included in your repository. There’s no hard rule on what belongs in a research repository. In some organizations, research repositories also store data coming from sources other than user-research studies — for example,  customer support-emails, notes from customer-advisory groups, or market research. When choosing what to include in a repository, consider the needs of your team and repository users.

Research repositories can be built and hosted in many different tools. Choose a tool that your team (and any colleagues who need to use the repository) can easily access or use.

According to our survey, the most popular tools for research repositories across organizations were:

• Collaboration tools (such as Confluence and Sharepoint) are often already used in many organizations. Since teams and stakeholders can easily access them, they become a natural starting place for many research repositories.
• User-research tools (such as Dovetail and EnjoyHQ) are used by researchers to transcribe and tag video recordings and perform qualitative data analysis . Many of these tools have repository features, making them an obvious repository choice.
• Database tools (such as Notion and Airtable) are often used by teams that already work with databases for product management. Database tools allow for easy cataloging of research projects, deliverables, and insight.

A research repository can take many forms and is often dependent on the tool chosen for the job.

Some repositories act as glorified document libraries, where research reports and study materials are filed away in a specific folder structure. These are common when repositories are housed within collaboration platforms like Sharepoint or Confluence.

Other research repositories are searchable indexes or databases of research findings. These are common when teams pursue atomic research — where knowledge is broken down into “nuggets” or key insights.

Each type of research repository has advantages and disadvantages (as shown in the table below). The main tradeoff is insight discoverability versus effort needed to add to the repository . Folder libraries are easy to contribute to and manage, but insights are less discoverable. On the other hand, insight databases are hard to contribute to and manage but provide easy access to research insights.

Of course, a research repository could include both an insights database and a research-document library. For example, an insights database could link to a folder structure containing all the research documentation from the study where the insight originated.

Getting people to contribute and use a research repository can be challenging. Regardless of the tool and type of repository you pursue, here are five attributes that make research repositories easy to use and adopt.

Easy to Access

The tool you use for your repository should be easy to access, use, and learn by teams and stakeholders. A new tool that is unfamiliar or that is hard to learn could stop people from accessing or contributing to your repository.

Flexible Permissions

The right people should have access to the right data. For most organizations, the research repository should not be publicly accessible since research could involve proprietary designs or cause reputational damage. If the repository stores session recordings or identifiable participant data, the right people in your organization should have access to those assets to ensure that participant data is handled appropriately .

Intuitive Navigation or Tags

People should be able to easily find and discover research. If it is too difficult for stakeholders and teams to locate research, they will give up.

If your repository is a document library, folders should be labeled and organized sensibly. If you are using a database or user-research platform, then create clear and useful global tags, to help contributors label their research and people find specific research-related information.

Repository users should be able to search by specific keywords (such as user groups, products, or features) to quickly find research insight. A strong and reliable search feature is often essential.

Exportable, Shareable, and Integrated

Sharing or exporting insight from the repository is important if research is to be disseminated widely. For example, if the repository tool supports integrations with other platforms, research snippets from the repository can be easily shared to Slack or MS Teams channels.

Step 1: Gain Buy-in

People won’t adopt a research repository if they don’t understand its value. Clearly present your arguments for the repository, including what teams might gain from having one. Gaining buy-in for the initiative and tool is especially important if you need to procure budget to purchase a specialized tool. You may need to show the return on investment (ROI) .

Step 2: Do Your Research

Do research before choosing a tool or structure for your repository. Treat the process of developing a repository like building a new product. Start with some discovery and take a user-centered approach.

Some helpful questions to explore:

• How do teams currently do research? What tools do they use?
• How do teams write up or share research insights currently? What works? What doesn’t?
• What questions do stakeholders ask researchers or teams when requesting research insights?
• What counts as research? What kind of research insights need to be stored and socialized?
• Which tools do researchers or teams have access to? What tools seem familiar and are easy to adopt?

If you are procuring a new tool for your repository, your research might include evaluating available tools to learn about their capabilities, pricing models, and constraints. You can also utilize free trials and demos and perform a trial run or private beta test with a new tool to find out what works.

Step 3: Start Simple and Iterate

When creating a tagging taxonomy for your repository, start with a few broad tags rather than getting too granular and specific. This approach will ensure that there aren’t too many tags to learn or apply. The tagging taxonomy may need to change over time as more research and contributors are added to the repository. It’s easier to make iterations if you have a small set of tags.

Consider testing your proposed tagging taxonomy or navigational structure. Methods like tree testing and card sorting can uncover the best labels, tags, or folder structures.

When thinking about adding content to a new repository, start simple. Instead of migrating all research (and research types) in one go, consider importing the most common or most useful items. Use this as a test run to refine the contribution process and structure for your repository.

Step 4: Onboard and Advocate

The key to successful adoption is a plan for onboarding and change management. Don’t expect the tool to be adopted straight away. Change aversion is common with any new process, design, or tool. Teams and stakeholders may need constant reminders or encouragement to use the repository. You may also need to run training sessions to help people learn how to use it and get value out of it.

Research repositories store and organize UX research, making research insights widely available and easy to consume throughout an organization. When creating a research repository, research available tools, gain feedback from researchers and teams who would use it, and plan to iterate after launch.

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Jan 23, 2024

How to build a UX research repository (that people actually use)

Extend the shelf life of your research and set your team up for long-term success with a robust research repository. Here’s how to build yours from scratch.

Ella Webber

Every UX research report was once a mountain of raw, unstructured data. User research repositories help collate that data, disseminate insights, democratize research, and spread the value of user research throughout your organization.

However, building (and maintaining) an accessible user research repository is no simple task. Getting people to use it is a whole other ball game.

In this guide, we’ll break down the specifics of user research repositories, some best practices and the benefits of building your own research library, plus how to get started, and our favorite examples of robust research repositories.

Fill your research repository with critical user insights

Drive business success and make informed decisions with Maze to extract valuable insights from user research

What is a research repository in UX research?

A user research repository is a centralized database which includes all your user research data, UX research reports , and artifacts. Different teams—like design, product, sales, and marketing—can find insights from past projects to contextualize present scenarios and make informed decisions.

Storing all your research data in a single place ensures every team has access to user insights and can use them to make research-driven decisions. Typically maintained by a research operations team, a well-structured research repository is an important step toward breaking down silos and democratizing user research for the entire organization.

If you’re looking to improve research maturity across your organization and start scaling UX research , building a watertight user research repository is your first step.

What’s included in a research repository?

Building a UX research repository can be challenging. Between compiling all the data, creating a collaborative space, and making it easily accessible to the teams who need it, you might be struggling to identify a start point.

Here’s a checklist of all the essentials to streamline the setup:

✅ Mission and vision ✅ Research roadmap ✅ Key methodologies ✅ Tools and templates ✅ Research findings ✅ Raw data and artifacts

Mission and vision

Whether you have a dedicated user research team or involve multiple departments in the UX research process , you need a clear mission and vision statement to create a shared purpose and foster collaboration. Not only should you include your wider UX research strategy and vision, but a ‘North Star’ for your repository, too.

For example, the mission statement for your repository could be, “Streamline our UX design process and promote informed decision-making with a centralized hub of user feedback and insights.”

Research roadmap

A clear UX roadmap makes it easy to prioritize your research efforts and seamlessly organize your repository. It analyzes your objectives and outlines all upcoming projects in a given timeline. You can use this roadmap to catalog your previous research campaigns and plan ahead .

Key methodologies

You should also list all the research methods you follow to create repeatable success. You can save SOPs for different methodologies to minimize the scope of error and set your team members up for success. Mia Mishek , UX Research Operations Program Manager at Pax8 , explains:

“Every repository should include common documents related to the research at hand, such as a brief, moderation guide/test script, and readout. Having all the documents easily accessible allows others to cross-reference while consuming research and use past research as a jumping-off point for further research.”

Tools and templates

Create a list of collaboration and product management tools for different steps in the product research process , such as usability testing , interviews, note-taking, data analysis, and more. Outline these and don’t forget to give quick access links to all your UX research tools .

Outlining instructions and key templates for specific research methods or analysis techniques can be useful. Consider including any tried-and-tested question repositories or best practices.

Research findings

Your repository should include a set of findings from every study. While you can add the final reports for all projects, it’s also a good practice to add quick takeaways and tags to make your collection easily searchable.

If you’ve conducted different types of analysis, it’s worth linking these here, too. Whether that’s a photo of your thematic analysis workshop, a walkthrough video of your results, or a link to digital affinity diagram.

Raw data and artifacts

Alongside research reports, you can store all the raw data from each study, like user interview recordings and transcriptions. Your team members can revisit this data to plan upcoming projects effectively or connect the dots between past and present insights.

Depending on how you store this, you may want to consider keeping piles of raw data in a ‘view only’ or locked area of the repository, to avoid risk of accidental tampering or deletion.

What are the benefits of a research repository?

User research is an ongoing process. The trickiest part for most teams when pursuing continuous research is breaking down silos and establishing a democratized approach to prevent wasteful overlap, unnecessary effort, and a lack of knowledge-sharing.

A good research repository fosters a culture of collaboration and supports user-centric design through collectively prioritizing and understanding your users.

Here are a few core benefits of building a user research repository:

Quickly access user research data

An easily searchable UX research repository makes it easy to filter through a mountain of data and find specific insights without pouring hours into it. Mia emphasizes the importance of making the information easily accessible:

“You should be able to go into the repository, understand what research has been done on X topic, and get the information you’re after. If you need someone else to walk you through the repository, or if there’s missing information, then it’s not doing its job.”

By creating a self-serve database, you can make all the data accessible to everyone and save time spent on reviewing prior research to feed existing efforts.

Inspire ideas and prioritize future research

A research repository can also help in identifying knowledge gaps in your existing research and highlight topics worth further exploration. Analyzing your past data can spark ideas for innovative features and guide your research efforts.

Different teams can utilize a research repository to help guide the product roadmap on areas that still need to be explored in the app, or areas that need to be revisited.

Mia Mishek , UX Research Operations Program Leader at Pax8

Build a shared knowledge library

One crucial advantage of a repository is that it helps democratize user research. Not only does it highlight the value of research and showcase the efforts of your product and research teams, but by centralizing research findings, you’re making it easier for everyone to make data-informed, user-centric decisions.

A research repository also provides versatility and other use cases to your research insights—from product managers to sales leaders, all stakeholders can access user insights for making research-driven decisions across the organization. Whether that’s informing a sales pitch, product roadmap, or business strategy; there’s endless applications for UX research.

This practice of knowledge-sharing and democratizing user insights is a big step in building a truly user-centered approach to product development.

Contextualize new data with past evidence

Your repository records all the raw data from past projects, making it easier to compare and contrast new findings with previous user research. This data also allows researchers to develop more nuanced reports by connecting the dots between present and past data.

Mia explains how these repositories cut down on the redundant effort of trying to dig up old research data on any topic: “A repository benefits UX researchers and designers because it’s not uncommon to ask what research was done on XYZ area before conducting more research. No one wants to do reductive work, so without a repository, it’s easy to forget past research on similar topics.”

What’s more, research libraries avoid the same research being repeated; instead allowing as many people as possible to benefit from the research, while minimizing the resources and time used.

4 Best research repository tools and templates

You don’t need a specialized tool to create a user research repository. A well-organized, shared Google Drive or Notion teamspace with detailed documentation can be just as effective. However, if you can, a dedicated tool is going to make your life a lot easier.

Here are four research repository tools to consider for storing existing and new research insights on, and working cross-functionally with multiple teams.

1. Confluence

Confluence is a team workspace tool by Atlassian that streamlines remote work. You can use this platform to create research docs from scratch, share them with your team, and save them for future reference. Plus, the tool lets you design wikis for each research study to organize everything—raw data, findings, and reports—in a structured manner.

You also get a centralized space to store data and docs from extra accounts, so multiple people can contribute to and access your repository.

Condens is a centralized UX research and analysis platform for storing, structuring, and analyzing user research data–and sharing those insights across your organization. You can collaborate on data analysis, create pattern recognition, and create artifacts for comprehensive outcomes.

With a detailed research repository guide to help you on your way, it's a great tool for teams of any size. Plus, you can also embed live Maze reports, alongside other UX research and analysis tools.

3. Dovetail

Dovetail is a user research platform for collecting, analyzing, and storing research projects. You can save and retrieve all documents from a single database, while tags, labels, and descriptions also simplify the task of cataloging past data.

The platform gives you a strong search function to quickly find any file or data from the entire hub. You can also use multiple templates to migrate data from different platforms to Dovetail.

4. Airtable

Airtable is a low-code tool for building apps that enables you to create a custom database for your UX research projects. It’s ideal for product teams looking to set up the entire repository from scratch because you need to configure everything independently.

You get a high degree of flexibility to integrate different data sources, design a customized interface, and access data in dynamic views. What’s more, you can build an interactive relational database to request resources from others and stay on top of the status of existing work.

Here’s a research repository database to get started.

Creating a UX research repository: 5 Best practices

Designing a bespoke repository to organize your research requires careful planning, a thorough setup workflow, and continuous maintenance. But once it’s ready, you’ll wonder how your product team survived without it. To get you started, here’s our five best practices to implement this process effectively and kickstart your repository.

1. Define clear objectives for your repository

Start by outlining what you want to achieve with a shared research library. You might want to standardize research methodologies across the board or build alignment between multiple teams to create more consistent outputs.

This goal-setting exercise gives all team members a purpose to pursue in upcoming projects. When they know what success looks like, they can strategically plan research questions and choose analysis methods.

Knowing your objectives will also help shortlist the best research and usability testing tools . You can invest in a good platform by evaluating a few core capabilities needed to achieve your goals (more on that shortly).

2. Create a structure and define taxonomy

You can structure your UX repository as a database with multiple fields. For example, here are a few fields to easily categorize responses when documenting user experience research:

• Key insights
• User quotes
• Criticality
• Sources of knowledge
• Possible solutions that were considered

Besides creating a structure to document a research study, you also need a well-defined taxonomy to help people find information. Defining your research taxonomy will help you categorize information effectively and design consistent naming conventions.

For example, you can create a set of predefined categories for every research study like:

• Focus country: USA, Australia, Canada, France
• Collected feedback: Feature request, feature enhancement, bugs
• Methodology: Usability testing, user interview, survey
• User journey stage: Before activation, power user, after renewal

💡 Less jargon, more alignment

Involve multiple stakeholders when defining the terminology for your library, and check it aligns with any internal Style Guides or glossaries. This ensures alignment from the outset, and makes it easy for everyone to filter results and find what they need.

3. Distribute knowledge through atomic research

Atomic research is an approach to UX research that prioritizes user research data organization. It proposes that you conduct research so that every piece of the project becomes easily reusable and accessible to all stakeholders.

According to the atomic research approach , you need to consider four components to organize your repository:

• Experiments (We did this): Explain the research methodology and the steps you followed in conducting the study
• Facts (We saw this): Document the main findings evident from the data gathered in the study
• Insights (Which made us think): Capture the key insights extracted from analyzing the research data
• Opportunities (So we did that): List the decisions and action items resulting from the research analysis

Using atomic research, you can create nuggets to organize information in your repository.

Nuggets are the smallest unit of information containing one specific insight, like a user quote, data point, or observation. The different types of nuggets to categorize your research data include observations , evidence , and tags . By breaking down a vast study into smaller nuggets, you can make your repository informative at a glance. You can use your defined taxonomy to label these nuggets.

4. Identify the creators and consumers in your team

Before outlining your repository’s structure, you need to define workflows for creating, reviewing, and maintaining the library. Spend some time defining who will:

• Own the setup process and create the overall guidelines
• Access past documents and add contributions consistently
• Maintain the documents for easy accessibility
• Only need to access customer insights

Assigning these roles makes it easy to estimate your team's bandwidth for building and maintaining such a massive library. You can also manage permissions in your repository platform to give everyone access to relevant materials and protect confidential resources.

Mia explains why this is important to make your repository more meaningful for end-users:

“You need to keep in mind the JTBD (jobs to be done) framework when building a repository. What do the folks accessing your repository need to do? Who are those people? You need to build your repository with the purpose of those distinct users.”

5. Shortlist and finalize tools based on your goals

When evaluating different research repository tools, consider your requirements and compare different platforms against the essential features you need for this repository. If you’re creating one for the first time, it’s okay to create an experimental setup to understand the impact.

Here are a few key factors to consider when shortlisting research repository tools:

• Ease of setup and use: Choose a platform with a gentle learning curve, especially if you have a big team with multiple members. A quick setup and user-friendly interface can maximize adoption and make your repository more accessible.
• Collaboration capabilities: A good repository lets you interact with different team members through comments, chat boxes, or tags. You can also manage permissions and set up different roles to share relevant research with specific stakeholders and team members .
• Tagging and searchability: Your repository is only as good as its ability to show precise search results for any keyword. Consider the ease of labeling new information and test the search function to check the accuracy of the results.
• Export and integrations: You’ll need to export some data or streamline your entire research ops setup by integrating different tools. So, evaluate each tool’s integration capabilities and the options to export information.

Plus, your ideal tool might be a combination of tools. For example, Steven Zhang , former Senior Software Engineer at Airtable, used a combination of Gong and Airtable when first building a UX research repository . It’s about considering your needs and finding what works for your team.

Democratize user research in your organization

A UX research repository gives you easy access to insights from past projects, and enables you to map new insights to old findings for a more nuanced understanding of your users.

More importantly, building a single source of truth for your entire organization means everyone on your team can access research data to inform their projects.

Different teams can use this data to make strategic design decisions, iterate product messaging, or deliver meaningful customer support.

Sound good? That’s what we thought—build your repository today to evangelize and democratize UX research in your organization.

Need a seamless solution to collect meaningful research insights?

Maze helps you collect and analyze research to find purposeful data for your product roadmap

Frequently asked questions about UX research repository

How do I create a user research repository?

You can create a user research repository with these best practices:

• Define clear objectives for your repository
• Create a structure and define taxonomy
• Distribute knowledge through atomic research
• Identify the creators and consumers in your team
• Shortlist and finalize tools based on your goals

What makes a good research repository?

A good research repository tells the team's mission and vision for using research. It's also easily searchable with relevant tags and labels to categorize documents, and includes tools, templates, and other resources for better adoption.

What’s the purpose of a research repository?

A research repository aims to make your UX research accessible to everyone. It democratizes research operations and fosters knowledge-sharing, giving everyone on your team access to critical insights and firsthand user feedback.

Tetra Insights

Research Repositories in Action: 6 Best Practices

Data in research is the lifeblood that fuels our decisions, insights, and innovations. To harness its power effectively, you need a robust research repository to store, organize, and manage that data. Whether you’re part of a bustling research team or a solo researcher, implementing best practices in your research repository can make a world of difference. Not only in terms of efficiency but collaboration and decision-making as well.

Let’s delve into these best practices and see how they can turn your research repository into a well-oiled machine.

Table of Contents

Understanding research repositories.

Before we dive into the best practices, let’s make sure we’re on the same page about what research repositories are.

A research repository, at its core, serves as a centralized hub for collecting and preserving your research data in various forms. This could encompass raw data, documents, research reports, presentations, datasets, and more. It’s akin to an organized library where each piece of information is carefully cataloged. Making it readily accessible to researchers, analysts, and stakeholders. Without a well-structured repository, valuable research assets might become scattered, leading to inefficiency and the risk of data loss.

These repositories act as the backbone of informed decision-making and knowledge sharing within organizations. They offer several key advantages.

The Benefits of Effective Research Repositories

1. enhanced collaboration.

A well-structured research repository promotes seamless collaboration among team members. You can share resources, insights, and findings, which is crucial when working on projects that require collective input.

2. Data Accessibility

Imagine having quick access to any research document or piece of data you need, precisely when you need it. A well-organized repository ensures that you can easily retrieve data, speeding up your research process.

3. Streamlined Decision-Making

With all your research assets in one place, decision-making becomes more straightforward. No more searching through endless folders or email chains to find that critical piece of information.

According to research conducted by AWS , 88% of online shoppers wouldn’t return to a website after a bad user experience. The ability to access and analyze user data efficiently can make all the difference in this context.

Now that we have a grasp of research repositories and their benefits, let’s explore six best practices that can help you master the art of managing your research assets.

Best Practice 1 – Define a Clear Taxonomy

A robust and well-defined taxonomy is the backbone of your research repository. It’s more than just categorization; it’s about structuring your repository to ensure that every piece of research data has a logical place. Consider the e-commerce industry. You can create parent categories like “Customer Data,” “Product Information,” and “Sales Statistics.” Within these, establish subcategories such as “Customer Feedback,” “Product Catalogs,” and “Monthly Sales Reports.”

This taxonomy not only organizes your data but also facilitates efficient retrieval. When it comes to the execution, many tools, including Tetra’s research repository, allow for customizable taxonomies that seamlessly align with your research objectives.

Best Practice 2 – Implement Version Control

Version control is your safety net against accidental overwrites, lost revisions, or unintentional data mishaps. You can take inspiration from popular version control systems like Git and apply similar principles to your research assets. Develop a standardized naming convention for your documents, such as “Report_v1,” “Report_v2,” and so on.

Utilize version control features offered by research repository tools like Tetra to easily track and manage different iterations of your documents. This way, you always know which version is the most recent and have access to historical changes, ensuring transparency and accountability in your research processes.

Best Practice 3 – Secure Data Access

Research repositories often contain sensitive and confidential data that must be safeguarded against unauthorized access or data loss. Take steps to limit access to authorized personnel by setting robust access controls. Establish backup and disaster recovery mechanisms to ensure that even in the event of a catastrophic data loss scenario, your research assets are recoverable.

Implement encryption and authentication measures to add an extra layer of security. A study by IBM showed data breaches can cost companies an average of $3.86 million. Secure your data to prevent such costly setbacks.

Best Practice 4 – Foster Collaboration

The true power of a research repository lies not just in its storage capacity but in its ability to facilitate seamless collaboration. Encourage cross-functional teamwork within your organization by providing a platform where team members can share insights, findings, and feedback directly within the repository.

This collaborative ecosystem promotes knowledge sharing, idea exchange, and the pooling of diverse skill sets. As the saying goes, “Two heads are better than one,” and by fostering collaboration, your research outcomes can benefit from multiple perspectives and expertise.

Best Practice 5 – Document Thoroughly

With documenting your research, the mantra is simple: document everything. From setting clear research objectives, and detailing data sources and methodologies, to documenting findings and insights, comprehensive documentation is a non-negotiable practice. It’s the foundation of credible research and informed decision-making.

A fully featured research repository tool like Tetra includes features that allow you to attach notes, comments, or annotations to specific documents. This enhances the depth of documentation. The next time you’re wondering about the origin of a particular data point or the rationale behind a specific approach, your comprehensive documentation will be your guiding light.

Best Practice 6 – Data Retrieval and Searchability

An often-underestimated aspect of a research repository is its searchability. Your data should not merely be stored; it should be easily retrievable. Tetra allows you to quickly locate the specific data you need, whenever you need it. Free of charge . This includes the ability to search by keywords, tags, and metadata.

Make sure your data is effectively indexed to enable efficient searching. If your team members are spending excessive time looking for data, it’s a sign that your repository lacks adequate searchability. Enhanced search capabilities, coupled with features like advanced filters and content indexing, significantly contribute to improving your research efficiency.

In Conclusion

An efficiently managed research repository can significantly impact your research capabilities. It streamlines your processes, fosters collaboration, and ultimately helps you make informed decisions. The key to success lies in understanding, implementing, and constantly improving these best practices. Your research assets are the foundation of your work—treat them with care, and they will serve you well.

At Tetra, we understand the importance of well-structured research repositories. Our tools and expertise can help you optimize your research repository management. Don’t miss the opportunity to enhance your research practices. Elevate your research with Tetra’s solutions.

Ready to Put These Best Practices Into Action?

Elevate your research management with Tetra’s Free Account. Experience the power of seamless organization and collaboration within your research repository. With Tetra, you gain access to:

• User-Friendly Taxonomy : Effortlessly categorize your research data with a clear and intuitive taxonomy system.
• Version Control : Easily manage and track changes in your research documents to prevent data loss.
• Robust Security : Keep your sensitive research data protected with Tetra’s top-tier security features.
• Collaborative Workspace : Foster teamwork and share insights with cross-functional collaboration.
• Comprehensive Documentation Tools : Capture and preserve all the necessary research details.
• Advanced Data Retrieval : Quickly and easily find the insights you need with advanced search and indexing capabilities.

Implement these best practices today by subscribing to Tetra’s Free Account. Take your research management to the next level.

Subscribe Now to organize, secure, and collaborate on your research assets effectively.

Want to Learn More? Join our Webinar!

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Taxonomies: the make-or-break of an insights repository

Knowledge is only as powerful as our ability to make use of it. Taxonomies make information accessible and can inspire the exchange of insights across teams and organisations - but what does it take to actually build one?

By definition, taxonomies are systems used to classify and organise data. The earliest taxonomies date back to the origins of human language . From the animal kingdom to a digital sitemap, whenever you see the categorisation of things, this is essentially a form of taxonomy. Taxonomies are certainly nothing new, but we continue to find new ways use them for one simple reason: ‍

Taxonomies make information accessible.  ‍

In the context of user research, building and maintaining a collection of tags (or in other words, a taxonomy), is essential in order to achieve user research excellence . At Dualo, we firmly believe that a strong taxonomy is the backbone of every great knowledge repository. 

In this article, we’ll look at:

- Why building a taxonomy for the outputs of your user research is so important

- The cost of not having a strong taxonomy

- Who should build and manage taxonomies

- How taxonomies are structured, and 

- A practical guide to building your own taxonomy

Why are taxonomies so important when building insight repositories?

Your organisation likely has many touchpoints and a wide variety of channels for obtaining knowledge. This might be through direct customer feedback, quantitative and qualitative analysis, or capturing technology and industry insights.

This knowledge is often valuable beyond the scope of a single study or context. In fact, product insights that relate to human nature and behaviour are likely relevant for entire organisations, and can remain true for years. 

But all of that knowledge is meaningless unless you can make sense of it. And the volume of available data that organisations can accumulate can often be overwhelming.

It’s therefore important that the outputs of user research are consolidated and organised in a way that’s accessible to wider teams and stakeholders. After all, insights are only as powerful as our ability to make use of them.

A taxonomy allows you to divide and group large collections of knowledge into more manageable themes. They help to visualise and organise your data.

Depending on the goals of your insights repository, a well structured taxonomy can:

- Efficiently and effectively filter existing knowledge  - Help identify patterns in your data and surface new insights for further consideration - Provide guidance to consistently and holistically categorise new data - Provide strategic direction to stakeholders and wider teams

The cost of not having a strong taxonomy 

“those who cannot remember the past are condemned to repeat it”.

George Santayana

If the benefits of having a taxonomy aren’t compelling enough, the cost of not having one is enough to make leaders stand up and take action in organisations large and small.

Research by nature is exploratory. Taxonomies structure and categorise information in a way that allows us to explore a particular subject or theme - bypassing the need for a specific search term or a preconceived idea of what exactly you're looking for.

Consider the scenario of onboarding onto a new team or project. The insights your organisation holds are likely spread across multiple previous studies. Insights specific to your needs may have been discovered in much broader contexts and remain buried deep within larger reports.There’s no doubt it would be helpful to have access to previous explorations and existing knowledge relevant to the area you’ll be working - but without the ability to filter knowledge, it’s difficult to know where to look. 

Many teams and individual researchers we’ve spoken with find themselves in this position more regularly than leadership often realises. In fact, according to a study conducted by Qatalog and Cornell university, employees waste around 59 minutes a day searching for knowledge .

It’s very common for teams to therefore start from scratch and create new silos. A recent IDC study found that data and research professionals lose a further 20% of their time duplicating research.

So aside from the significant opportunity cost caused by a lack of structured, inaccessible data, there are significant hard costs too. Considering the average researcher salary in the UK, searching for knowledge and repeating work costs organisations £16,250 per researcher, every year.

Searching for knowledge and repeating work costs organisations £16,250 per researcher, every year.

Who should build your organisation’s taxonomy?

Research professionals within customer-centric organisations have increasingly become the orchestrators of knowledge, responsible for storing data and insights in a retrievable way. They will likely lead the charge as they already have the clearest understanding of how knowledge should be structured. 

That said, building a taxonomy for a knowledge repository should be a collaborative process. When initiating the process, it’s important to consider not just teams who will be contributing to the repository, but also the teams and individuals that will be consuming data from it. 

Taxonomies should be built with multiple teams and disciplines in mind. Using universally understandable language for tags and themes encourages wider teams and stakeholders to self-serve knowledge and build an understanding of how data is structured across your organisation. It’s often helpful to therefore involve representatives from these teams, at the very least when reviewing or refining your taxonomy. 

Local or global? 

A question we often get asked is “where do our local taxonomies fit into all of this?”. By ‘local’ what people are often referring to is taxonomies specifically built for teams, departments or projects (rather than representing a more global, multi-team view). 

Whilst we’ve seen localised taxonomies work, our view is that (for the most part), organisations should work towards one minimum global taxonomy . Why silo your data and allow inconsistencies as well as duplication to occur when you can build one powerful and all encompassing system?

How is a taxonomy structured? 

Since no organisation is the same, there’s no ‘one size fits all’ solution to building a taxonomy. And because data can tell many different stories, it’s important to establish what you want to learn from the data before you decide how to structure it. 

Once you’ve established what you’re hoping to achieve by building your taxonomy, you’ll need to define its scope. Are you building a multi-disciplinary taxonomy to classify your data at an organisational level? Or is the scope narrowed to only ‘qualitative research’ or ‘industry insights’?

Scope plays a major role in the granularity of categories; in qualitative research tools, tags might be used to categorise raw data, observations and singular sentences from a user interview. In a multi-disciplinary repository, tags are more likely to span across multiple themes, and cover broader products and teams. 

One of the key jobs when building a taxonomy is to establish a set of overarching themes. Themes are essentially patterns in the data. 

Generally speaking, insight repositories are most effective when built using a hierarchical taxonomy, which enables us to create these sub-categories or ‘themes’. 

For many reading this post, a hierarchical taxonomy will likely have a strong resemblance to a UX affinity map/diagram. 

And for good reason, the process of building taxonomies is very similar to a card sorting or affinity mapping exercise. Both use similar methods to organise research findings into overarching themes.

Below are some common themes we’ve seen teams include in their taxonomy:

- Product / Feature / Touch point

- Sentiment / Experience / Pain point / NPS

- Segment / Geography / Audience type / Persona

- Need / Goal / Motivation / JTBD

- Device / Browser / Technology 

- Research Type / Method  / Researcher / Source / Date

- Team / Tribe / Department / Discipline 

- Scale / Frequency / Severity / Business impact / goals

- Industry / sector / Competitor / Proposition

Remember that when it comes to tagging, not all themes will be relevant to every piece of research.

Is there a maximum recommended number of tags or themes?

There is no set amount of tags or themes, nor a maximum number to stick to when building a taxonomy. We find it helpful to follow the ‘just enough’ principle. Building a taxonomy is as much an art as it is a science, so you’ll need to experiment with what’s right for your organisation and use case.

Too many tags can be overwhelming and slow down researchers uploading data. Too few tags diminish your ability to usefully filter knowledge in specific areas. Generally speaking, it’s advisable to build broad and shallow rather than narrow and deep. If your taxonomy has too many levels, potentially useful themes and patterns could end up getting buried. 

A practical guide to building your own taxonomy 

For experienced research teams, experimenting with methods for building and maintaining a taxonomy is common practice. We’ve worked with many teams and seen several techniques work particularly well. We've developed a workshop inspired by some of these practices and structured around the affinity diagramming method. The workshop is flexible and intended only as a guide. The workshop takes roughly 1.5-2 hours, we hope you find it useful.

Taxonomy workshop:

1. Establish the desired outcomes

What is the scope of the taxonomy?

When do we want to begin using the new taxonomy? ‍

2. Analyse sample data

Depending on the scope of your taxonomy, we’ve found that a mixture of data types works well. Try to bring between 5-10 sources to deconstruct. Sample data could range from existing studies and reports, to strategic insights, analytics reports, or UX artefacts - whatever is relevant to your scope, goals, and organisation.  ‍

3. Establish an initial set of tags from the sample data 

This doesn’t have to be perfect or exhaustive. What categories jump out when looking at each piece of sample data?  ‍

4. Create sample themes

Consider the themes and how you want to categorise your data by looking at the initial set of tags you've established. These can shape, grow and merge as time goes on. Consider creating a few category names to help get the sorting started. Some common themes for insight repositories are listed above. ‍

5. Add a “?” theme

Adding a miscellaneous category is helpful so as not to get stuck on tags that are less easily categorised. Tags in this category can be revisited later with a more holistic view of the data.  ‍

6. Begin sorting & identifying themes in the data

1. Choose a tag at random

2. Look for a category that makes sense 

3. Move the tag to sit within that category, or create a new one. If no obvious category name arises, place it in the “?” category for discussion later. ‍

7. Assess your categories 

Do your themes and categorisations make sense? Are there any stronger themes that have emerged? Is there any crossover? Can any categories be merged?  ‍

‍ 8. Assign colours to each theme

Assigning colours to different themes in the data is helpful for a number of reasons;

1. Contributors can use colour to guide them and ensure multiple themes have been considered when tagging data.

2. Consumers can quickly build visual associations to the themes in your repository, allowing them to visually skim the data and quickly determine if it’s relevant to what they’re looking for.

3. Colours can also be used to signal sentiment. For example, some teams use red for anger, and green or blue for calm. ‍

Following the workshop:

Build your taxonomy and begin indexing your data

If you choose to conduct your taxonomy workshop in-person or outside of the insights repository tool, the next step is to ensure that the tags and themes are built using a tag manager that enables quick and easy setup and maintenance. ‍

Maintain your taxonomy 

Taxonomies are not set in stone, they are living artefacts that are constantly adapting and evolving. It’s important to plan for a learning curve and set reviews with your team on a regular basis. Returning to your taxonomy and spotting new themes in the data is an opportunity to discover new patterns in your user’s behaviours. Consider some common questions when reviewing your taxonomy:

Have any new themes emerged?

Would it be helpful to merge some tags or themes? 

Can we remove any tags or themes? 

It’s important to be flexible when reviewing and maintaining a taxonomy. The strengths and weaknesses of your taxonomy will become clearer as you tag more data. As time goes on, you’ll most likely need to adjust the structure according to changing processes, scope and requirements.

Consider who has editing rights to your taxonomy 

Taxonomies take time to build. They allow us to create intricate webs of data, delicately threaded together. Complex data can quickly get tangled up in the wrong hands. To avoid laborious unpicking, ensure that you only give editing rights to people who understand the implications of changing things.

Knowledge is only as powerful as your ability to make use of it. Taxonomies are the backbone of every great insights repository, and one of the most critical jobs to get right when building one. 

Building taxonomies is not just about organising data, it’s about building a holistic view of the knowledge your organisation holds. 

If built and managed correctly, they can make knowledge accessible and inspire the exchange of insights across teams and organisations - enabling teams to elevate to ‘research excellence’ status, and ultimately build better products. Done wrong, they can seriously hamper the ability for researchers to make an impact, and reduce the amount of repeatable value an organisation can realise from research.

We continue to shape our understanding on how teams can ensure they build the best possible taxonomies to maximise the value and impact of their knowledge. We hope that this post proves valuable for anyone looking to build or maintain a research taxonomy.

Happy tagging!

References & further reading

https://dovetailapp.com/blog/what-we-learned-creating-tagging-taxonomy/

https://blog.getenjoyhq.com/user-research-taxonomy/  

https://supermassive.ca/ux-design/building-a-user-centered-taxonomy/

https://www.nngroup.com/articles/affinity-diagram/

About Dualo

Dualo is an insights hub used by digital product teams to get more repeatable value from their user research and insights, so that stakeholders can make informed and timely decisions across the organisation. If you're interested in learning more, please request a demo and a member of our team will be in touch.

I’m a design, UX & strategy lead with a passion for storytelling. Proud member of Dualo’s founding product trio. Always seeking new inspiration.

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